# Apify vs Labelbox

Apify records 4,147,762 monthly visits with +3.9% month-over-month growth and Freemium, Contact for Pricing pricing. Labelbox records 762,803 monthly visits with -22.8% growth and Contact for Pricing pricing.

| Metric | [Apify](https://openaitools.app/tool/apify) | [Labelbox](https://openaitools.app/tool/labelbox) |
| :--- | :--- | :--- |
| Website URL | https://www.apify.com | https://labelbox.com |
| Categories | AI Web Scraping, AI Agent, AI API, AI Developer Tools | AI Developer Tools, AI API, AI Workflow, AI Productivity Tools |
| Pricing Model | Freemium, Contact for Pricing | Contact for Pricing |
| Monthly Visits | 4,147,762 | 762,803 |
| MoM Growth Rate | +3.9% | -22.8% |
| Primary Market | United States | United States |
| Direct Visits | 1,816,433 | 370,024 |
| Review Score | 4.6 | 4.4 |
| Saved Count | 6 | 0 |
| Supported Platforms | Website | Website |

## Apify

Apify started as a general-purpose web automation cloud and has grown into one of the largest marketplaces of turnkey web data extractors. The platform exposes a store of Actors — small containerized programs built by Apify and by third-party developers — that handle jobs like pulling Google Maps listings, TikTok videos, Instagram posts, Amazon prices, or crawling a documentation site into clean Markdown for a RAG pipeline. Each Actor runs on Apify's cloud, can be triggered from an API, scheduled on a recurring basis, and wired into downstream storage or applications.\n\nBecause running scrapers in production is mostly an infrastructure problem, Apify bundles the unglamorous parts: rotating residential and datacenter proxies, browser fingerprinting and anti-blocking, retry logic, dataset and key-value storage, and monitoring. Developers who would rather write their own code can build Actors with the Apify SDK in Python or JavaScript, or use Crawlee, Apify's open-source crawling and browser-automation library, which works with Playwright, Puppeteer, Selenium, and BeautifulSoup.\n\nRecently the platform has positioned itself around AI: the Apify MCP server and CLI let AI agents and assistants discover and call Actors as tools, and the Website Content Crawler Actor is explicitly designed to feed LLM applications and vector databases. Pricing follows a freemium model with monthly platform credits, pay-per-usage pricing for many Actors, and custom enterprise agreements.

**Pricing & Plans:** Freemium: a free plan with monthly usage credits, paid subscription tiers that scale credits and concurrency, consumption-based charges for many marketplace Actors, and custom enterprise pricing. Developer payouts are also available for published Actors.

- **Actor marketplace:** Over one hundred thousand ready-to-run scrapers and automation tools covering social media, maps, e-commerce, real estate, and general web crawling.
- **MCP server and CLI:** Connect Apify Actors directly to AI assistants and agents so they can search the store, run scrapers, and pull structured results as tool calls.
- **Anti-blocking and proxy infrastructure:** Managed proxy rotation and unblocking are built into the platform, so scrapers keep working when target sites add defenses.
- **Crawlee and the Apify SDK:** An open-source crawling library plus Python and JavaScript SDKs for building custom Actors with Playwright, Puppeteer, Selenium, or Cheerio.
- **Scheduling, storage, and integrations:** Recurring runs, dataset exports to CSV/JSON/Excel, webhooks, and integrations with LangChain, LlamaIndex, Zapier, and thousands of apps.

**Strengths:** Enormous library of maintained scrapers means many jobs need no code at all; Infrastructure concerns like proxies, retries, and blocking are handled for you; Agent-ready through MCP, CLI, and API, with LangChain and LlamaIndex integrations; Generous free tier for testing plus a developer revenue-share program

**Limitations:** Costs scale with usage, so high-volume scraping can get expensive quickly; Quality varies between community-built Actors and first-party ones; Target sites change frequently, so some Actors break or need updating over time

[Profile (Markdown)](https://openaitools.app/tool/apify.md)

## Labelbox

Labelbox occupies an unusual position in the AI stack: it does not primarily sell a chatbot or a generator, it builds the environments and data that models learn from plus the agents that take over recurring engineering and research work. The homepage claim is direct — frontier AI labs train on Labelbox environments and expert data, while engineering and research teams hand their recurring backlog to agents running on Recursion. A recent Series E of more than $100 million signals a heavily funded bet on that thesis.,For enterprises, the newer half of the product is Recursion. Agents are triggered by real signals — a failing build, a PagerDuty alert, a new dependency release, a fresh model checkpoint, or a Monday morning schedule — and then work in the background until the job is done. The examples the company promotes are concrete deliverables rather than summaries: a tested pull request with a preview link, a postmortem draft in Confluence with every event sourced, an ablation table naming the changes that mattered, or a patch for each exposed service after a critical CVE. A grader agent scores each run, and the graded session leaves behind memories, notes and skills that the next session reads before it acts.,The original foundation remains the data business: labeling, annotation, curation and model evaluation supported by expert human reviewers, used for computer vision, NLP, supervised fine-tuning, RLHF and red teaming. In practice the two halves reinforce each other, since the environments that produce high-quality training data are the same environments where agents learn to do real work. Pricing is enterprise-style, routed through sales conversations and shaped by data volume and agent usage, with no public self-serve tier.

**Pricing & Plans:** Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases.

- **Data labeling and expert annotation:** Structured annotation, curation, model evaluation and human-in-the-loop review across vision, language and generative tasks, used to build the training and eval data behind production models.
- **Autonomous agent sessions:** Recursion agents start on their own from builds, alerts, commits, checkpoints and schedules, then work in the background until the task is finished and reviewable.
- **Domain specialists by function:** Specialist agents cover software engineering, reliability, security, ML research, evals, R&D, product and finance workflows, from flaky test fixes to postmortem drafts and vulnerability patches.
- **Graded outcomes that compound:** Every agent run is scored by a grader, and graded sessions leave memories, notes and skills that the next session reads before acting, so quality compounds over time.
- **Native tool and data integrations:** Agents operate against the tools teams already use, including GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery, Databricks, Vercel and cloud providers.

**Strengths:** Covers both sides of the problem: training and eval data production plus agents that act on recurring work; Backed by a recent $100M+ Series E and adoption by frontier AI labs, indicating real funding and demand; Agent runs produce concrete deliverables with proof — tests, reruns, ablations — rather than unverified suggestions; Integrates with the toolchain teams already run: GitHub, Jira, Linear, Slack, Datadog, PagerDuty, BigQuery and Databricks

**Limitations:** No self-serve pricing or open signup: everything routes through a sales conversation, which slows down evaluation; The platform assumes real engineering and research infrastructure (GitHub, cloud providers, data warehouses) to deliver value; Positioning has shifted quickly toward autonomous agent sessions, so teams wanting only labeling workflows may find it heavier than needed

[Profile (Markdown)](https://openaitools.app/tool/labelbox.md)

## Frequently Asked Questions

### How do Apify and Labelbox compare in monthly traffic?

Apify has 4,147,762 monthly visits, while Labelbox has 762,803. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Apify has a month-over-month growth rate of +3.9%; Labelbox has -22.8%.

### How does pricing compare?

Apify: Freemium, Contact for Pricing. Freemium: a free plan with monthly usage credits, paid subscription tiers that scale credits and concurrency, consumption-based charges for many marketplace Actors, and custom enterprise pricing. Developer payouts are also available for published Actors. Labelbox: Contact for Pricing. Contact for pricing. Labelbox does not publish self-serve plans or public rate cards; its pricing route instead directs interested teams to talk to sales, and cost is shaped by data production scope, agent deployment and enterprise requirements. There is no published free tier. Prospective customers should request a quote based on their volumes and use cases.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [n8n](https://openaitools.app/tool/n8n) | 4,522,449 | -7.4% | Freemium | Open-source workflow automation built for AI agents and technical teams | [.md](https://openaitools.app/tool/n8n.md) |
| 2 | [Firecrawl](https://openaitools.app/tool/firecrawl-dev) | 1,828,239 | -1.9% | Freemium, Contact for Pricing | Provides direct LLM-ready markdown conversion via API, but lacks Apify's massive marketplace of pre-built scraping actors. | [.md](https://openaitools.app/tool/firecrawl-dev.md) |
| 3 | [Roboflow](https://openaitools.app/tool/roboflow) | 1,431,204 | +6.6% | Freemium, Contact for Pricing | Streamlines end-to-end computer vision workflows from annotation to model deployment, but lacks Labelbox's general enterprise agent orchestration. | [.md](https://openaitools.app/tool/roboflow.md) |
| 4 | [Clay](https://openaitools.app/tool/clay-2-0) | 1,267,465 | -2.7% | Freemium, Free Trial, Contact for Pricing | Build GTM systems that turn data into revenue | [.md](https://openaitools.app/tool/clay-2-0.md) |
| 5 | [Bright Data](https://openaitools.app/tool/bright-data) | 802,752 | -5.9% | Free Trial, Paid | Offers enterprise-grade proxy networks and raw web data infrastructure, but lacks Apify's plug-and-play actor marketplace. | [.md](https://openaitools.app/tool/bright-data.md) |
| 6 | [Appen](https://openaitools.app/tool/appen-com) | 665,840 | +0.2% | Contact for Pricing | Relies heavily on managed human-in-the-loop workforce services for data validation, offering less self-serve technical tooling than Labelbox. | [.md](https://openaitools.app/tool/appen-com.md) |
| 7 | [Scale](https://openaitools.app/tool/scale) | 616,915 | +12.5% | Contact for Pricing | Delivers enterprise-grade labeling and model evaluation at massive scale, but often requires higher enterprise budgets than Labelbox. | [.md](https://openaitools.app/tool/scale.md) |
| 8 | [SuperAnnotate](https://openaitools.app/tool/super-annotate) | 386,034 | +37.4% | Free Trial, Contact for Pricing | Offers robust multimodal annotation and workflow automation, featuring slightly more intuitive data curation pipelines for computer vision teams. | [.md](https://openaitools.app/tool/super-annotate.md) |
| 9 | [Gumloop](https://openaitools.app/tool/gumloop) | 379,557 | -21.1% | Freemium, Paid, Contact for Pricing | Automates complex business workflows with AI agents, but is less specialized for raw large-scale web scraping actors. | [.md](https://openaitools.app/tool/gumloop.md) |
| 10 | [Weights & Biases (CoreWeave Forge)](https://openaitools.app/tool/prompts) | 315,624 | -80.2% | Freemium, Contact for Pricing, Free | Track, evaluate, and ship AI models and agents in one connected environment. | [.md](https://openaitools.app/tool/prompts.md) |

---
Source: https://openaitools.app/compare/apify-vs-labelbox

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)